If you saw Darren Aronofsky's frenetic, disturbing flick Pi, you know that its hero, a supergenius who invents a super algorithm, meets a rather terrible end. Though he wants to use his algorithm for the forces of good, he's pursued by evil corporate schemers who want to use it to predict the stock market. Eventually our hero has to destroy his work in a tragic, horrifying scene I won't spoil for you. But the New York Times is reporting today on a real-life inventor of super algorithms whose entanglement with the financial industry did not end tragically. In fact, billionaire David E. Shaw used the cash he gained from developing computer-based strategies for Wall Street trading to found a company whose new mega-computer places them on the cusp of making tremendous medical discoveries about proteins (pictured).

D.E. Shaw & Company has just announced the completion of a massively parallel supercomputer nicknamed Anton, which is designed expressly to model biological processes. Specifically, it will carry out fast simulations of protein folding, modeling how protein molecules fold themselves into the unique shapes that allow them to interact with cellular structures or other proteins and keep your body running smoothly. Being able to model protein behavior quickly will help speed up research on medicines that change the way proteins are folded — fixing ones that fold incorrectly and make you sick, for instance. Though Anton hasn't gone for a test drive in a lab yet, it's been written up in scientific journals.

The New York Times' John Markoff writes:

The new supercomputer is distinguished from other molecular dynamics computing tools like I.B.M.'s BlueGene/L supercomputer and the Stanford Folding@home distributed computing project in that the machine is designed to simulate a very narrow set of problems on biological processes that take place over a millisecond or longer. Molecular simulations are now done as a series of tiny intervals that may be as short as a femtosecond, one billionth of one millionth of a second, and may last no longer than a microsecond, or one millionth of a second.

By looking at time scales that last several orders of magnitude longer than today's simulations, the Anton team is hoping to discover new kinds of biological processes that would not otherwise be observable. "If you can do 1,000 times longer, real proteins come into play," Mr. Shaw said in a technical lecture in 2006 at Stanford describing his work.

If only the guy from Pi had known he could have turned his work to something awesome like this, he might not have met such a miserable end. Sometimes life is more hopeful than fiction.